基于贝叶斯网络的社区配电网系统动态风险评估

社区配电网系统的安全分析和动态风险评估是配电网系统安全运行的关键环节。传统的可靠性指标无法反映社区配电网系统中物理元器件的状态和短路故障事件等本质安全问题对风险评估的影响。针对现有风险评估方法的局限性,提出一种基于贝叶斯网络的社区配电网系统安全分析与动态风险评估框架。首先,在标准可靠性指标的基础上,创新性地将社区配电网系统中物理元器件的故障率和短路故障事件引入到风险评估中,提出一种新的社区配电网停电风险评估指标体系,该评估指标体系综合考虑了社区配电网的可靠性指标和本质安全特性,能够全面反映社区配电网系统的动态风险;其次,提出一种基于故障树-贝叶斯网络的社区配电网系统动态风险评估方法;最后,以一个实际社区的配电网系统为案例,验证了该动态风险评估框架的可行性和有效性。案例分析结果表明:所提出的框架能够充分评估社区配电网系统的停电风险,并可以给出合理的安全措施,以有效降低社区配电网系统的动态风险。

Dynamic Risk Assessment of Community Power Distribution Network System Using Bayesian Network

The safety analysis and dynamic risk assessment of community distribution power network system are the key links of safe operation of power distribution network system.The traditional reliability index can not reflect the impact of intrinstic safety such as the operation status of physical components and short-circuit fault events on risk assessment.In view of the limitations of existing risk assessment me-thods,this paper proposes a safety analysis and dynamic risk assessment framework for community power distribution network system based on Bayesian network.Firstly,based on the standard reliability index,the failure rate and short-circuit fault events of physical components in community power distribution network are introduced into risk assessment,and a new assessment index system for power outage risk of community power distribution network is proposed.The index system comprehensively considers the reliability index and intrinsic safety characteristics,and can fully reflect the dynamic risk of community power distribution network system.Secondly,a dynamic risk assessment method based on fault tree-Bayesian network is proposed.Finally,the feasibility and effectiveness of the dynamic risk assessment framework are verified by taking a power distribution network system in a real community as an example.The case analysis results show that the proposed framework can fully assess the power outage risk of community power distribution network system,and can provide reasonable security measures to effectively reduce the dynamic risk of community power distribution network system.